#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
SM4Algorithm的泄漏模型
定义SM4各个操作的Power泄漏特征
"""

import numpy as np
from typing import Dict, Any, List


class SM4LeakageModels:
    """SM4泄漏模型集合"""
    
    # SM4 S-box
    SM4_SBOX = np.array([
        0xd6, 0x90, 0xe9, 0xfe, 0xcc, 0xe1, 0x3d, 0xb7, 0x16, 0xb6, 0x14, 0xc2, 0x28, 0xfb, 0x2c, 0x05,
        0x2b, 0x67, 0x9a, 0x76, 0x2a, 0xbe, 0x04, 0xc3, 0xaa, 0x44, 0x13, 0x26, 0x49, 0x86, 0x06, 0x99,
        0x9c, 0x42, 0x50, 0xf4, 0x91, 0xef, 0x98, 0x7a, 0x33, 0x54, 0x0b, 0x43, 0xed, 0xcf, 0xac, 0x62,
        0xe4, 0xb3, 0x1c, 0xa9, 0xc9, 0x08, 0xe8, 0x95, 0x80, 0xdf, 0x94, 0xfa, 0x75, 0x8f, 0x3f, 0xa6,
        0x47, 0x07, 0xa7, 0xfc, 0xf3, 0x73, 0x17, 0xba, 0x83, 0x59, 0x3c, 0x19, 0xe6, 0x85, 0x4f, 0xa8,
        0x68, 0x6b, 0x81, 0xb2, 0x71, 0x64, 0xda, 0x8b, 0xf8, 0xeb, 0x0f, 0x4b, 0x70, 0x56, 0x9d, 0x35,
        0x1e, 0x24, 0x0e, 0x5e, 0x63, 0x58, 0xd1, 0xa2, 0x25, 0x22, 0x7c, 0x3b, 0x01, 0x21, 0x78, 0x87,
        0xd4, 0x00, 0x46, 0x57, 0x9f, 0xd3, 0x27, 0x52, 0x4c, 0x36, 0x02, 0xe7, 0xa0, 0xc4, 0xc8, 0x9e,
        0xea, 0xbf, 0x8a, 0xd2, 0x40, 0xc7, 0x38, 0xb5, 0xa3, 0xf7, 0xf2, 0xce, 0xf9, 0x61, 0x15, 0xa1,
        0xe0, 0xae, 0x5d, 0xa4, 0x9b, 0x34, 0x1a, 0x55, 0xad, 0x93, 0x32, 0x30, 0xf5, 0x8c, 0xb1, 0xe3,
        0x1d, 0xf6, 0xe2, 0x2e, 0x82, 0x66, 0xca, 0x60, 0xc0, 0x29, 0x23, 0xab, 0x0d, 0x53, 0x4e, 0x6f,
        0xd5, 0xdb, 0x37, 0x45, 0xde, 0xfd, 0x8e, 0x2f, 0x03, 0xff, 0x6a, 0x72, 0x6d, 0x6c, 0x5b, 0x51,
        0x8d, 0x1b, 0xaf, 0x92, 0xbb, 0xdd, 0xbc, 0x7f, 0x11, 0xd9, 0x5c, 0x41, 0x1f, 0x10, 0x5a, 0xd8,
        0x0a, 0xc1, 0x31, 0x88, 0xa5, 0xcd, 0x7b, 0xbd, 0x2d, 0x74, 0xd0, 0x12, 0xb8, 0xe5, 0xb4, 0xb0,
        0x89, 0x69, 0x97, 0x4a, 0x0c, 0x96, 0x77, 0x7e, 0x65, 0xb9, 0xf1, 0x09, 0xc5, 0x6e, 0xc6, 0x84,
        0x18, 0xf0, 0x7d, 0xec, 0x3a, 0xdc, 0x4d, 0x20, 0x79, 0xee, 0x5f, 0x3e, 0xd7, 0xcb, 0x39, 0x48
    ], dtype=np.uint8)
    
    @staticmethod
    def hamming_weight(value: int) -> int:
        """Calculate汉明权重"""
        return bin(value).count('1')
    
    @staticmethod
    def hamming_distance(a: int, b: int) -> int:
        """CalculateHamming distance"""
        return SM4LeakageModels.hamming_weight(a ^ b)
    
    @classmethod
    def sbox_output_model(cls, input_byte: int) -> int:
        """
        SM4 S-boxOutput泄漏模型
        
        Args:
            input_byte: S-boxInput字节
            
        Returns:
            S-boxOutput值
        """
        return cls.SM4_SBOX[input_byte]
    
    @classmethod
    def sbox_output_hamming_weight(cls, input_byte: int) -> int:
        """
        SM4 S-boxOutput汉明权重泄漏模型
        
        Args:
            input_byte: S-boxInput字节
            
        Returns:
            S-boxOutput的汉明权重
        """
        sbox_output = cls.sbox_output_model(input_byte)
        return cls.hamming_weight(sbox_output)
    
    @classmethod
    def sbox_input_model(cls, plaintext_byte: int, key_byte: int) -> int:
        """
        SM4 S-boxInput泄漏模型（用于First轮Attack）
        
        Args:
            plaintext_byte: Plaintext字节
            key_byte: 轮Key字节
            
        Returns:
            S-boxInput值（PlaintextXORKey）
        """
        return plaintext_byte ^ key_byte
    
    @classmethod
    def first_round_sbox_output_model(cls, plaintext_byte: int, key_byte: int) -> int:
        """
        SM4First轮S-boxOutput泄漏模型（CompleteAttack链）
        
        Args:
            plaintext_byte: Plaintext字节
            key_byte: 轮Key字节
            
        Returns:
            S-boxOutput值
        """
        sbox_input = cls.sbox_input_model(plaintext_byte, key_byte)
        return cls.sbox_output_model(sbox_input)
    
    @classmethod
    def round_function_input_model(cls, plaintext_word: int, key_word: int) -> int:
        """
        SM4轮FunctionInput泄漏模型
        
        Args:
            plaintext_word: Plaintext字（32位）
            key_word: 轮Key字（32位）
            
        Returns:
            轮FunctionInput值
        """
        return plaintext_word ^ key_word
    
    @classmethod
    def tau_transform_model(cls, word: int) -> int:
        """
        SM4的tau变换（非线性变换）：4个并行S-box
        
        Args:
            word: 32位Input字
            
        Returns:
            tau变换后的32位字
        """
        # 将32位字分解For4个字节
        bytes_list = cls.word_to_bytes(word)
        
        # 对Each字节应用S-box
        sbox_bytes = [cls.sbox_output_model(byte) for byte in bytes_list]
        
        # 组合回32位字
        return cls.bytes_to_word(sbox_bytes)
    
    @classmethod
    def linear_transform_model(cls, sbox_output: int) -> int:
        """
        SM4线性变换L泄漏模型
        
        Args:
            sbox_output: S-boxOutput（32位）
            
        Returns:
            线性变换后的值
        """
        # SM4线性变换 L(B) = B ⊕ (B<<<2) ⊕ (B<<<10) ⊕ (B<<<18) ⊕ (B<<<24)
        def rotl(value: int, shift: int) -> int:
            """32位左Loop移位"""
            return ((value << shift) | (value >> (32 - shift))) & 0xffffffff
        
        result = sbox_output
        result ^= rotl(sbox_output, 2)
        result ^= rotl(sbox_output, 10)
        result ^= rotl(sbox_output, 18)
        result ^= rotl(sbox_output, 24)
        
        return result & 0xffffffff
    
    @classmethod
    def round_function_f_model(cls, x0: int, x1: int, x2: int, round_key: int) -> int:
        """
        SM4Complete轮FunctionF泄漏模型
        
        F(X0, X1, X2, X3, rk) = X0 ⊕ T(X1 ⊕ X2 ⊕ X3 ⊕ rk)
        其中 T = L ∘ tau（线性变换LAnd非线性变换tau的复合）
        
        Args:
            x0: Status字X0（32位）
            x1: Status字X1（32位）
            x2: Status字X2（32位）
            round_key: 轮Keyrk（32位）
            
        Returns:
            轮FunctionF的Output（32位）
            
        Note：这里简化For3个Input，实际SM4HasX0, X1, X2, X3四个Status字
        """
        # Step1: Calculate X1 ⊕ X2 ⊕ X3 ⊕ rk（这里简化For X1 ⊕ X2 ⊕ rk）
        temp = x1 ^ x2 ^ round_key
        
        # Step2: 非线性变换tau（4个并行S-box）
        tau_output = cls.tau_transform_model(temp)
        
        # Step3: 线性变换L
        l_output = cls.linear_transform_model(tau_output)
        
        # Step4: 与X0异Or
        result = x0 ^ l_output
        
        return result & 0xffffffff
    
    @classmethod
    def key_schedule_model(cls, key: bytes, round_num: int) -> int:
        """
        SM4Key调度泄漏模型
        
        Args:
            key: 主Key（16字节）
            round_num: 轮数（0-31）
            
        Returns:
            轮Key
        """
        # 简化的SM4Key调度模型
        # 实际SM4Key调度更复杂，这里ProvideBasic框架
        
        # FK常数
        FK = [0xa3b1bac6, 0x56aa3350, 0x677d9197, 0xb27022dc]
        
        # CK常数（Partial）
        CK = [
            0x00070e15, 0x1c232a31, 0x383f464d, 0x545b6269,
            0x70777e85, 0x8c939aa1, 0xa8afb6bd, 0xc4cbd2d9,
            0xe0e7eef5, 0xfc030a11, 0x181f262d, 0x343b4249,
            0x50575e65, 0x6c737a81, 0x888f969d, 0xa4abb2b9,
            0xc0c7ced5, 0xdce3eaf1, 0xf8ff060d, 0x141b2229,
            0x30373e45, 0x4c535a61, 0x686f767d, 0x848b9299,
            0xa0a7aeb5, 0xbcc3cad1, 0xd8dfe6ed, 0xf4fb0209,
            0x10171e25, 0x2c333a41, 0x484f565d, 0x646b7279
        ]
        
        # 简化实现：Use轮数AndKey的Simple组合
        key_int = int.from_bytes(key[:4], 'big')  # 取前4字节
        if round_num < len(CK):
            return (key_int ^ FK[round_num % 4] ^ CK[round_num]) & 0xffffffff
        else:
            return (key_int ^ FK[round_num % 4]) & 0xffffffff
    
    @classmethod
    def word_to_bytes(cls, word: int) -> List[int]:
        """将32位字ConvertFor4个字节"""
        return [
            (word >> 24) & 0xff,
            (word >> 16) & 0xff,
            (word >> 8) & 0xff,
            word & 0xff
        ]
    
    @classmethod
    def bytes_to_word(cls, bytes_list: List[int]) -> int:
        """将4个字节ConvertFor32位字"""
        return (bytes_list[0] << 24) | (bytes_list[1] << 16) | (bytes_list[2] << 8) | bytes_list[3]
    
    @classmethod
    def get_intermediate_functions(cls) -> Dict[str, Any]:
        """获取Intermediate valueCalculateFunction"""
        return {
            'sbox_output': cls.sbox_output_model,
            'sbox_input': cls.sbox_input_model,
            'first_round_sbox_output': cls.first_round_sbox_output_model,
            'round_function_input': cls.round_function_input_model,
            'tau_transform': cls.tau_transform_model,
            'linear_transform': cls.linear_transform_model,
            'round_function_f': cls.round_function_f_model,
            'key_schedule': cls.key_schedule_model,
        }
    
    @classmethod
    def get_leakage_models(cls) -> Dict[str, Any]:
        """获取泄漏表示模型"""
        return {
            'value': lambda x: x,
            'hamming_weight': cls.hamming_weight,
            'hamming_distance': cls.hamming_distance,
            'bit_0': lambda x: x & 1,
            'bit_31': lambda x: (x >> 31) & 1,
        }
    
    @classmethod
    def get_target_operations(cls) -> List[str]:
        """获取可Attack的目标操作"""
        return [
            'first_round_sbox',
            'last_round_sbox',
            'round_function',
            'linear_transform',
            'key_schedule',
            'round_key_addition',
        ]
    
    @classmethod
    def get_operation_to_intermediate_mapping(cls) -> Dict[str, str]:
        """获取目标操作ToIntermediate valueFunction的Mapping"""
        return {
            'first_round_sbox': 'sbox_output',
            'last_round_sbox': 'sbox_output',
            'round_function': 'round_function_input',
            'linear_transform': 'linear_transform',
            'key_schedule': 'key_schedule',
            'round_key_addition': 'round_function_input',
        }
    
